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wassnameandClaudypoo
abe43ad593
Replace the blind ipsative-PCA projection with two named IW axes built from GlobalOpinionQA WVS items (tinymfv.iw_axes): X = Survival<->Self-expression (homosexuality, trust, political action), Y = Traditional<->Secular-Rational (religion importance+belief, abortion, child autonomy). Each item is oriented to its axis-positive pole by reading the option order, so a reversed row can't flip a country. Human anchors land where the published IW map puts them (Sweden top-right, Nigeria/Pakistan bottom-left, East Asia secular-but-survival top-left). Models answer the same items via the answer-token reader (single-digit option labels so the 1-10 justifiable scale stays single-token); coords are the same axis-mean. Add maps.draw_zone_hulls: tight rounded convex hulls (not inflated disc unions), zone-coloured dots, outlier-only labels, white-haloed region names -- the Economist grammar. draw_zone_regions stays for the instrument maps' within-country spread. Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
54 lines
1.9 KiB
Python
54 lines
1.9 KiB
Python
"""Dump FULL (untruncated) text + options + coverage for WVS questions matching each IW theme, so
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the precise per-item selector and axis-positive pole can be locked by eye. -- authored by Claude
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uv run python scripts/probe_iw_themes.py
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"""
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from __future__ import annotations
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import ast
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import re
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from datasets import load_dataset
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from tinymfv.zones import zone_of
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SKIP = re.compile(r"don'?t know|no answer|refus|decline|none of|not applicable|^other|missing|inap",
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re.I)
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THEMES = {
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"Y_religion": r"how important it is in your life|believe in any|importance of god|attend religious",
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"Y_abortion": r"\babortion\b",
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"Y_childaut": r"encouraged to learn at home",
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"X_homosex": r"homosexual",
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"X_trust": r"most people can be trusted",
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"X_politaction": r"forms of political action",
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}
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def main() -> None:
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ds = load_dataset("Anthropic/llm_global_opinions", split="train")
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recs = []
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for r in ds:
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if r["source"] != "WVS" or not r["question"]:
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continue
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opts = ast.literal_eval(r["options"]) if isinstance(r["options"], str) else r["options"]
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keep = [i for i, o in enumerate(opts) if not SKIP.search(o)]
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sel = ast.literal_eval(re.search(r"\{.*\}", r["selections"], re.S).group(0))
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ncov = sum(1 for c in sel if zone_of(c) and sum(sel[c][i] for i in keep) > 0)
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recs.append({"q": r["question"], "opts": [opts[i] for i in keep], "ncov": ncov})
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for theme, pat in THEMES.items():
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rx = re.compile(pat, re.I)
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hits = sorted([r for r in recs if rx.search(r["q"])], key=lambda r: -r["ncov"])
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print(f"\n{'='*90}\n{theme}: {len(hits)} matches\n{'='*90}")
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for r in hits:
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if r["ncov"] < 40:
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continue
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tail = r["q"][-90:].replace("\n", " / ")
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print(f"[cov {r['ncov']:3d}] n_opts={len(r['opts'])} ...TAIL: {tail!r}")
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print(f" opts: {r['opts']}")
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if __name__ == "__main__":
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main()
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